machine learning engineer

Checkout.com is a global fintech company that provides a digital payments platform for businesses. The organization enables large-scale transaction processing for global merchants, powering digital experiences for various industries.

• Build systems for training, deploying, and monitoring machine learning models at scale;
• Build and optimize data pipelines and backend services to process dispute and payment data in real time;
• Build and scale a feature store for online and offline use-cases;
• Take complete ownership of delivering end-to-end features, driving the lifecycle from requirement refinement to production deployment;
• Turn raw data into production-ready features for dispute systems;
• Collaborate with platform and backend engineers to integrate models.

• 5+ Years of experience as an MLOps or ML Engineer;
• High proficiency in writing production-ready Python code;
• Experience with production ML models and standard MLOps practices;
• Experience with monitoring and observability of production systems;
• Experience with training and operating models on Databricks;
• Nice to have: Familiarity with cloud-based development (AWS or Azure), experience with ML frameworks and technologies such as scikit-learn, xgboost, TensorFlow, PyTorch, Spark, SageMaker, Vertex AI, Kubeflow, Seldon, or Triton.

• Hybrid working model with three days per week in the office.